One Robot builds task-specific world models and an evaluation platform for robot manipulation policies. Training end-to-end policies for robots is vibes-based today. Teams collect data, train, deploy on a real robot, find out what fails, collect more, retry. We replace the trial-and-error with rigorous validation that tells you where your policy will fail and what data to collect to fix it. Robotics can't industrialize without an evaluation layer. We're building it. We're based in San Francisco, backed by Accel, YC, several exited founders, and engineering leaders at leading AI companies. We're small and deliberately so — everyone owns a wide surface area and moves fast. …
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